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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
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Posts
Recommended resources to learn bioinformatics
Published:
–ENTRY IN PROGRESS– Read more
First blog post
Published:
I just got my first PhD paper published, which includes the publication of my first software. So I thought it was time to make my own site to organize these and future work. Read more
publications
Pathway Analysis: State of the Art
Published in Frontiers in Physiology, 2015
This review’s aim is to give an overview of what pathway analysis is and how different methods have developed encompassing the same idea of trying to identify biologically meaningful categories that are relevant for the results obtained from Omics experimental data. 
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Recommended citation: García-Campos, M.A., Espinal-Enríquez, J. and Hernández-Lemus, E., 2015. Pathway analysis: state of the art. Frontiers in physiology, 6, p.383. https://www.frontiersin.org/articles/10.3389/fphys.2015.00383
Deciphering the m6A code via quantitative profiling of m6A at single-nucleotide resolution
Published in bioRxiv, 2019
In this preprint we present a method to quantify m6a using a m6a sensitive endonuclease, and uncover the mechanistic behaviour of methylation trough a simple and conserved code in cis. 
’ Read more
Recommended citation: Garcia-Campos, M.A., Edelheit, S., Toth, U., Shachar, R., Nir, R., Lasman, L., Brandis, A., Hanna, J.H., Rossmanith, W. and Schwartz, S., 2019. Deciphering the "m6A code" via quantitative profiling of m6A at single-nucleotide resolution. BioRxiv, p.571679. https://www.biorxiv.org/content/10.1101/571679v1
Deciphering the “m6A Code” via Antibody-Independent Quantitative Profiling
Published in Cell, 2019
In this paper we present a method to quantify m6a using an m6a sensitive endonuclease, and uncover the mechanistic behaviour of methylation trough a simple and conserved code in cis.
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Recommended citation: Garcia-Campos, M. A. et al. (2019) ‘Deciphering the “m6A Code” via Antibody-Independent Quantitative Profiling’, Cell. Elsevier, 0(0). doi: 10.1016/j.cell.2019.06.013. https://www.cell.com/cell/fulltext/S0092-8674(19)30676-2
Tolerance to Oxidative Stress in Budding Yeast by Heterologous Expression of Catalases A and T from Debaryomyces hansenii
Published in Current Microbiology, 2020
In this study we show the recovery and enhancement of the budding yeast’s resistance to oxidative stress by expressing ortholog catalase genes from D. hansenii, a sea yeast. 
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Recommended citation: González, J., Castillo, R., García-Campos, M. A., Noriega-Samaniego, D., Escobar-Sánchez, V., Romero-Aguilar, L., ... & Segal-Kischinevzky, C. (2020). Tolerance to Oxidative Stress in Budding Yeast by Heterologous Expression of Catalases A and T from Debaryomyces hansenii. Current Microbiology, 77(12), 4000-4015. https://link.springer.com/article/10.1007/s00284-020-02237-3
Multiplexed profiling facilitates robust m6A quantification at site, gene and sample resolution
Published in Nature Methods, 2021
Here we develop m6A-seq2, a multiplexed immunoprecipitation-RNA-seq coupled method that measures m6A across the epitranscriptome reducing technical variability, cost, and labor. Allowing for sample-level m6A relative quantitations, orthogonal to mass-spectrometry methods, as well as gene-level quantitations. We found that m6A-seq2 m6A gene-level measurements explains roughly 30% of the variability in the RNA half life on mouse embryonic stem cells. 
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Recommended citation: Dierks, D., Garcia-Campos, M.A., Uzonyi, A., Safra, M., Edelheit, S., Rossi, A., Sideri, T., Varier, R.A., Brandis, A., Stelzer, Y. and van Werven, F., 2021. Multiplexed profiling facilitates robust m6A quantification at site, gene and sample resolution. Nature Methods, pp.1-8. https://www.nature.com/articles/s41592-021-01242-z
txtools: an R package facilitating analysis of RNA modifications, structures, and interactions
Published in bioRxiv, 2023
In this preprint we present txtools, an R package that enables the processing, analysis, and visualization of RNA-seq data at the nucleotide-level resolution, seamlessly integrating alignments to the genome with a transcriptomic representation.
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Recommended citation: Garcia-Campos, M. A., & Schwartz, S. (2023). txtools: an R package facilitating analysis of RNA modifications, structures, and interactions. bioRxiv, 2023-08. https://www.biorxiv.org/content/10.1101/2023.08.24.554738
Dissecting the sequence and structural determinants guiding m6A deposition and evolution via inter- and intra-species hybrids
Published in BMC - Genome Biology, 2024
In this paper we dissect the determinants governing RNA methylation via interspecies and intraspecies hybrids in yeast and mammalian systems, coupled with massively parallel reporter assays and m6A-QTL reanalysis.
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Recommended citation: Shachar, R., Dierks, D., Garcia-Campos, M. A., Uzonyi, A., Toth, U., Rossmanith, W., & Schwartz, S. (2024). Dissecting the sequence and structural determinants guiding m6A deposition and evolution via inter-and intra-species hybrids. Genome Biology, 25(1), 1-29. https://genomebiology.biomedcentral.com/articles/10.1186/s13059-024-03182-1
txtools: an R package facilitating analysis of RNA modifications, structures, and interactions
Published in Nucleic Acids Research, 2024
We present txtools, an R package that enables the processing, analysis, and visualization of RNA-seq data at the nucleotide-level resolution, seamlessly integrating alignments to the genome with transcriptomic representation. .
Read more
Recommended citation: Miguel Angel Garcia-Campos, Schraga Schwartz, txtools: an R package facilitating analysis of RNA modifications, structures, and interactions, Nucleic Acids Research, 2024;, gkae203, https://doi.org/10.1093/nar/gkae203. https://academic.oup.com/nar/advance-article/doi/10.1093/nar/gkae203/7632932
software
MAZTER-MINE
MAZTER-mine is a computational pipeline to analize MAZTER-seq derived data, a methodology that profiles m6A quantitatively across transcriptomes in a single-base manner. Read more
talks
Deciphering the ‘m6A code’ via quantitative profiling of m6A at single-nucleotide resolution
Published:
A departmental talk on my work on m6A which led to the publication of my first PhD paper. Read more
teaching
Principles and practice of large scale data analysis using R 2018-1. (TA)
MSc-PhD course, Weizmann Institute of Science, Feinberg Graduate School, 2017
The course is intended for graduate students in the Life Sciences area. The goal of the course is to enable students to use the R programming language as a tool to extract biological insight from high throughput data. Read more
Principles and practice of large scale data analysis using R 2019-1. (TA)
MSc-PhD course, Weizmann Institute of Science, Feinberg Graduate School, 2018
The course is intended for graduate students in the Life Sciences area. The goal of the course is to enable students to use the R programming language as a tool to extract biological insight from high throughput data. Read more
Principles and practice of large scale data analysis using R 2020-1. (TA)
MSc-PhD course, Weizmann Institute of Science, Feinberg Graduate School, 2019
The course is intended for graduate students in the Life Sciences area. The goal of the course is to enable students to use the R programming language as a tool to extract biological insight from high throughput data. Read more
Principles and practice of large scale data analysis using R 2021-1. (TA)
MSc-PhD course, Weizmann Institute of Science, Feinberg Graduate School, 2020
The course is intended for graduate students in Life Sciences. The goal of the course is to enable students to use the R programming language as a tool to extract biological insight from high throughput data. Read more